Workshop 4: Rhythms and Oscillations

(March 18,2013 - March 22,2013 )

Organizers


Carmen Canavier
Cell Biology and Anatomy, Louisiana State University
Bard Ermentrout
Department of Mathematics, University of Pittsburgh
Pascal Fries
Fries Lab, Max-Planck-Institut of Neurobiology
Todd Troyer
Biology, University of Texas

This workshop will focus on how mathematics can help us determine the functional roles that oscillations play in the nervous system. This workshop is timely in view of recent evidence that oscillations are critical for cognitive states and sensory processing. A broad range of oscillatory activity will be covered, including hippocampal and cortical oscillations, motor patterns, sensory processing and circadian rhythms. Competing theories will be presented on controversial issues, such as the role of gamma oscillations in binding of sensory information and the role of theta oscillations in hippocampal circuitry, with a view to how mathematics might help to resolve these controversies. We will try to draw parallels across different systems to see if central organizing principles emerge. Recent theoretical advances in the understanding of several central pattern generators (CPGs) will be compared and contrasted, including the CPG for coordinating crawfish swimmerets, the CPG for respiratory pattern generation, the pyloric circuit, and spinal CPGs involved in human gaits. Circadian rhythms will be addressed at the level of the molecular clocks underlying the diurnal rhythm and at the level of the interaction of these clocks with the electrical activity of the suprachiasmatic nucleus. Sensory systems will be represented by theoretical and experimental studies on the role of oscillations in distinguishing odors. Theoretical results on the nonlinear dynamics of coupled oscillators in the presence of noise will be presented and integrated into the context of the specific examples presented for different systems.

Accepted Speakers

Thomas Akam
Neurobiology of Action, Champalimaud Neuroscience Program
Tad Blair
Psychology & Brain Research Institute, University of California, Los Angeles
Christoph Borgers
Mathematics, Tufts University
Nicolas Brunel
Statistics and Neurobiology, University of Chicago
Neil Burgess
Institute of Cognitive Neuroscience, University College London
Tim Buschman
Psychology, Princeton University
Jessica Cardin
Neurobiology, Yale University
Laura Colgin
Neuroscience, University of Texas
Oded Ghitza
Biomedical Engineering, Boston University
Lisa Giocomo
Neurobiology, Stanford University
Michael Hasselmo
Psychology, Boston University
Alexandre Hyafil
DEC, ENS, Laboratoire de Neurosciences Cognitives
Nancy Kopell
Department of Mathematics and Statistics, Boston University
Frances Skinner
Toronto Western Research Institute, University Health Network
Paul Tiesinga
Neuroinformatics, Radboud University Nijmegen
Rufin VanRullen
Centre de Recherche Cerveau et Cognition, CNRS
Monday, March 18, 2013
Time Session
08:15 AM

Shuttle to MBI

08:30 AM
08:45 AM

Breakfast

08:45 AM
09:00 AM

Welcome, overview of workshop, and introductions: Marty Golubitsky

09:00 AM
10:00 AM
Neil Burgess - The theta rhythm, spatial cognition and the hippocampus

Electrophysiological recordings from neurons in the hippocampal and entorhinal cortices of freely moving rodents provide detailed information regarding the neural representations of spatial location and orientation, and indicate a functional role for neural coding with respect to the theta rhythm of the local field potential. I will describe some of these experiments and the computational mechanisms they imply. These emphasise the roles of environmental boundaries in self-localization, via boundary vector cell firing, and temporal oscillations in the theta band in path integration, via grid cell firing. Both types of information are combined in the firing of place cells. I will describe the implications of these findings for the mechanisms supporting human spatial memory, and provide examples of electrophysiological and functional neuroimaging experiments designed to test these implications.

10:00 AM
10:30 AM

Break

10:30 AM
11:30 AM
Michael Hasselmo - Oscillations and grid cells in entorhinal cortex

Oscillations and grid cells in entorhinal cortex

11:30 AM
12:30 PM
Tad Blair - A synchronization code for space: Theory and evidence

The rodent hippocampus and cortex contain spatially tuned neurons—such as place, grid, and border cells—that are tuned to fire selectively when a rat visits specific locations in space. Such neurons are commonly assumed to implement a ‘population vector code’ which represents the animal’s position within its environment as a distributed pattern of neural firing rates. However, most spatially tuned neurons exhibit rhythmic modulation of their firing rates by 4-10 Hz theta oscillations, and the phases of such oscillations carry information about the rat’s position. Efforts to explain this observation have given rise to a class of models which posit that spatially tuned neurons may derive their position-dependent firing by detecting synchrony among theta oscillators with frequencies that vary with the animal’s movement velocity, in such a way that their phases (and thus their synchrony with one another) depend strictly upon the animal’s position in its environment. Here, I will outline one version of such a model, which posits that the rodent spatial memory system contains two major classes of neurons: rhythm generators (RGs) and synchrony detectors (SDs). It shall be hypothesized that RGs correspond to ‘theta cells’ that burst rhythmically at velocity-dependent frequencies, whereas SDs correspond to spatially tuned neurons that burst selectively at locations where they detect synchrony among a preferred subset of RGs. I will then describe results from recent experiments that have been carried out in our lab to test two key predictions of this hypothesis: 1) that the burst frequencies of theta cells vary as the cosine of the rat’s movement direction, and 2) that synchrony among pairs of simultaneously recorded theta cells vary with the rat’s position on a 2D sinusoidal grating defined over the surface of the environment.

12:30 PM
02:00 PM

Lunch Break

02:00 PM
03:00 PM
Lisa Giocomo - Mechanisms underlying medial entorhinal cortex topography

A core goal of neuroscience is to determine how sensory inputs map to neural circuits and form functional cortical architectures. Recently, our understanding of the neural representation of space by medial entorhinal cortical neurons has evolved to the point of providing a unique opportunity to determine the mechanisms and function of circuit organization in a region highly associated with spatial navigation and memory. My research has specifically concentrated on the mechanisms underlying the representation of space by medial entorhinal cortex neurons called ‘grid cells’. A strong characteristic of grid cells is their spatial scale, which is organized topographically, increasing progressively from dorsal to ventral medial entorhinal cortex. I have focused on unraveling the potential substrates underlying this topographical expansion of grid scale. In addition, our recent work has highlighted the presence of a topographic gradient in another functionally-defined medial entorhinal cell type; the head direction cell.

03:00 PM
03:30 PM

Break

03:30 PM
04:30 PM
Laura Colgin - Slow and Fast Gamma Rhythms in the Hippocampal Network

Brain rhythms reflect periodically synchronized electrical activity across groups of neurons and are thought to be important for neuronal communication across disparate brain regions. Gamma rhythms are a particular type of rhythm that occurs throughout many regions of the brain and have been linked to functions such as attentional selection and memory. Gamma oscillations vary in frequency (from ~25 Hz to ~ 100 Hz) from one brain region to another and also within a given brain region from one moment to the next. The exact frequency of oscillations is important because different areas will communicate most effectively when their oscillatory timing is the same. In the hippocampus, a brain region critically involved in memory operations, two distinct subtypes of gamma oscillations, slow and fast gamma, occur at different times. During slow gamma (~40 Hz), hippocampal subfield CA1 is coupled with neighboring subfield CA3, an area involved in memory retrieval. During fast gamma (~80 Hz), CA1 is coupled with the entorhinal cortex, a region transmitting information about the current environment. In this lecture, I will present new data supporting the hypothesis that slow and fast gamma rhythms serve different functions, namely that slow gamma facilitates memory retrieval and fast gamma promotes memory encoding.

04:30 PM
06:00 PM

Reception and poster session in MBI Lounge

06:15 PM

Shuttle pick-up from MBI

Tuesday, March 19, 2013
Time Session
08:15 AM

Shuttle to MBI

08:30 AM
09:00 AM

Breakfast

09:00 AM
10:00 AM
Thomas Akam - Response dynamics of oscillating networks, oscillatory mechanisms for selective gain control

Response dynamics of oscillating networks, oscillatory mechanisms for selective gain control

10:00 AM
10:30 AM

Break

10:30 AM
11:30 AM
Christoph Borgers - Suppression boundaries in E-I networks, and the type of the I-cells

The synaptic interaction of excitatory and inhibitory neurons (E- and I-cells) can generate oscillations, provided that the drive to the I-cells is low enough, so that they don't get ahead of the E-cells but merely respond to them. If the drive to the I-cells is high, and inhibitory synapses are strong, the E-cells are suppressed altogether. We think about the transition from rhythmicity (low drive to the I-cells) to suppression of the E-cells (high drive to the I-cells). In work with Nancy Kopell several years ago, we suggested that this transition, if it is abrupt, could be exploited to allow the network to toggle between rhythmic activity and suppression, and that this could be useful in attentional selection. In contrast with the earlier work, here we assume that synchronization of the I-cells is always enforced by gap junctions. We find that in this case, the transition from rhythmicity to suppression is much more abrupt when the I-cells have a type 2 phase response (excitation early in the phase retards them) than when they have a type 1 phase response (excitation always accelerates them). We demonstrate this with simulations and explain it using a one-dimensional map.

11:30 AM
12:30 PM
Jessica Cardin - State-dependent cortical rhythms

State-dependent cortical rhythms

12:30 PM
02:00 PM

Lunch Break

02:00 PM
03:00 PM
Nicolas Brunel - Collective oscillations in networks of spiking neurons: Mechanisms and input dependence

Collective oscillations in networks of spiking neurons: Mechanisms and input dependence

03:00 PM
03:30 PM

Break

03:30 PM
04:30 PM
Frances Skinner - Gaining insight from theoretically-inspired biologically-based models

It is clear that we need mathematical models and analyses of them to understand brain dynamics. However, in building our mathematical models of neuronal networks, it is not clear what data, how much data, and what level(s) of detail are most appropriate to use. Furthermore, it is clear that cellular characteristics need to be considered in our models as experiments continue to show cellular specificity in affecting network output. However, network size and connectivity also have to be taken into consideration. In this talk, I will present our work examining the generation of gamma rhythms in models of fast-spiking inhibitory cell networks. These models are based on CA1 hippocampus considering an ING-type mechanism and using the experimental context of a whole hippocampus preparation exhibiting spontaneous population activities. Consideration of these aspects together leads to the requirement of weak inhibitory connections between fast-spiking cells and strong excitatory drives to them for coherent gamma rhythms to emerge. Most interestingly, a sharp transition in gamma coherence is found for small changes in excitatory drive, thus suggesting a potential design property underlying theta/gamma rhythms. It is important to note that without the experimental context and constraints, this does not arise. Our work thus illustrates how a mathematical mechanism coupled with a well-defined experimental context could lead to biological insights.

04:45 PM

Shuttle pick-up from MBI

Wednesday, March 20, 2013
Time Session
08:15 AM

Shuttle to MBI

08:30 AM
09:00 AM

Breakfast

09:00 AM
10:00 AM
Rufin VanRullen - Perceptual and attentional rhythms

Neuronal communication between cortical areas heavily relies on oscillatory, periodic mechanisms whose precise timing critically determines the flow of information. Yet little is known about the perceptual and psychological consequences of such periodic neuronal dynamics at the rapid time scale of the oscillatory cycle: what perceptual changes accompany the drastic changes of neuronal activity observed between opposite phases of the cycle? I will show several experimental examples of these perceptual consequences in the visual domain. To summarize, visual perception and attention seem to wax and wane intermittently at frequencies in the theta (~7Hz) and alpha (~10Hz) range, possibly reflecting the underlying periodic neuronal processes. Based on spiking neural network simulations, I will argue that similar perceptual cycles can also exist at higher frequencies (gamma range), and that our perceptual experience may be the result of cross-frequency interactions between these different rhythms

10:00 AM
10:30 AM

Break

10:30 AM
11:30 AM
Oded Ghitza - On the central role of theta in decoding speech

On the central role of theta in decoding speech

11:30 AM
01:00 PM

Lunch Break

01:00 PM
02:00 PM
William Lytton - Theta gamma coordination in setting of psychomimetics and other modulatory interventions

Theta gamma coordination in setting of psychomimetics and other modulatory interventions

02:00 PM
02:30 PM

Break

02:30 PM
03:30 PM
Alexandre Hyafil - Theta-gamma nested oscillations in speech perception

Theta-gamma nested oscillations in speech perception

03:30 PM
04:30 PM
Steve Bressler - Large-Scale Synchronous Beta Rhythms

Large-Scale Synchronous Beta Rhythms

04:45 PM

Shuttle pick-up from MBI

Thursday, March 21, 2013
Time Session
08:15 AM

Shuttle to MBI

08:30 AM
09:00 AM

Breakfast

09:00 AM
10:00 AM
Peter Lakatos - The role of oscillatory entrainment in auditory selective attention

The role of oscillatory entrainment in auditory selective attention

10:00 AM
10:30 AM

Break

10:30 AM
11:30 AM
Tim Buschman - Neural Dynamics of Cognitive Control

Cognitive control is the ability to direct behavior in a goal-directed manner. This ability lies at the core of intelligent behaviors, allowing us to focus our limited cognitive capacity on one task while still maintaining the flexibility to quickly switch to another task as the situation (or our goals) change. I will present results on the role of frontal and parietal cortices in two forms of cognitive control: the control of attention and flexible rule use. By leveraging large-scale, multiple-region electrophysiology in non-human primates we are able to observe synchronization of neural activity within and between brain regions while animals perform these complex behaviors. I will describe results suggesting synchrony supports cognitive behaviors and how its dynamic nature may underlie cognitive flexibility.

11:30 AM
12:30 PM
Paul Tiesinga - Oscillations and neural coding

Oscillations and neural coding

12:30 PM
02:00 PM

Lunch Break

02:00 PM
03:00 PM
Nancy Kopell - Brain Rhythms Facilitate Bottom-Up and Top-Down Processing

It is well known that the brain produces rhythms at many different frequencies and combination of frequencies, and that these rhythms are associated with different cognitive states and tasks. It is still mysterious, however, how the rhythms take part in function. This talk discusses two working hypotheses about this issue.

  1. Clues to the function of rhythms come from the physiology underlying the rhythms (Function Follows Physiology). That is, it is not just the frequency that matters, but also the mechanistic bases of rhythms that matter in their functional applications. In particular, cortical layers are critical.
  2. The ways in which rhythms support function are complex; they are not apt to be obvious from data, and require modeling to form hypotheses.

These themes are illustrated with examples involving bottom-up and top-down processing, including cortical and thalamic rhythms.

03:00 PM
03:30 PM

Break

03:30 PM
04:30 PM
Pascal Fries - Distinct top-down and bottom-up attention networks revealed through high-resolution electrocorticography

Brain-wide networks operating at a millisecond timescale are thought to underlie our cognitive functions, but have never been observed directly. Neuroimaging studies based on hemodynamic signals visualized the precise topographies of brain-wide functional networks, but at low temporal resolution. Neurons and areas within these networks likely cooperate through rhythmic synchronization in multiple frequency bands. However, limitations of current recording methods have restricted our ability to detect and investigate these putative brain-wide synchronization networks. Only if extended corticocortical synchronization networks are observed directly and in behaving subjects, will we simultaneously reveal their topographies, frequencies, directions of information flow and cognitive functions, and thereby the relations among those properties. I will present data from large-scale, high-density electrocorticography grids, combining millisecond temporal and millimeter spatial resolution with coverage of large parts of one hemisphere. I will show that a given brain area may simultaneously participate in different networks that synchronize in distinct frequencies and mediate influences in counter-streams. A gamma-band (50 90 Hz) network synchronizes visual-occipital areas and parts of parietal cortex, and gamma-mediated inter-areal influences are bottom-up. A beta-band (peaking at 14 18 Hz) network synchronizes parietal and frontal areas and parts of visual cortex, and beta-mediated inter-areal influences are mostly top-down. Both networks subserve the cognitive function of attention: gamma- and beta-mediated inter-areal influences are enhanced when they mediate behaviorally relevant signals. The direct topographical demonstration of rhythmic synchronization-defined networks constitutes a new quality of brain network investigation and opens an important window onto their function.

04:45 PM

Shuttle pick-up from MBI

06:30 PM
07:00 PM

Cash Bar

07:00 PM
08:30 PM

Banquet in the Fusion Room at Crowne Plaza Hotel

Friday, March 22, 2013
Time Session
08:15 AM

Shuttle to MBI

08:30 AM
09:00 AM

Breakfast

09:00 AM
12:00 PM

Synthesis and wrap-up by organizers

12:15 PM

Shuttle pick-up from MBI to hotel and Columbus Airport

Name Affiliation
Akam, Thomas thomas.akam@neuro.fchampalimaud.org Neurobiology of Action, Champalimaud Neuroscience Program
Bazhenov, Maxim Maksim.Bazhenov@ucr.edu The Salk Inst. for Biological Studies
Best, Janet jbest@math.ohio-state.edu Department of Mathematics, The Ohio State University
Billock, Vincent vincent.billock.ctr@wpafb.af.mil National Research Council, U.S. Air Force Research Laboratory
Blair, Hugh blair@psych.ucla.edu Psychology & Brain Research Institute, University of California, Los Angeles
Booth, Victoria vbooth@umich.edu Mathematics , University of Michigan
Borgers, Christoph cborgers@tufts.edu Mathematics, Tufts University
Borisyuk, Alla borisyuk@math.utah.edu Mathematics, University of Utah
Braun, Wilhelm pmxwb1@nottingham.ac.uk School of Mathematical Sciences, Centre for Mathematical Medicine and Biology, University of Nottingham
Bressler, Steve bressler@fau.edu Psychology, Florida Atlantic University
Brunel, Nicolas nbrunel@galton.uchicago.edu Statistics and Neurobiology, University of Chicago
Burgess, Neil n.burgess@ucl.ac.uk Institute of Cognitive Neuroscience, University College London
Buschman, Tim tim@timbuschman.com Psychology, Princeton University
Butera, Robert rbutera@gatech.edu Electrical and Computer Engineering, Georgia Institute of Technology
Canavier, Carmen ccanav@lsuhsc.edu Cell Biology and Anatomy, Louisiana State University
Cardin, Jess jess.cardin@yale.edu Neurobiology, Yale University
Colgin, Laura colgin@mail.clm.utexas.edu Neuroscience, University of Texas
Coombes, Stephen stephen.coombes@nottingham.ac.uk School of Mathematical Sciences, University of Nottingham
Critch, Andrew critch@math.berkeley.edu Mathematics, University of California, Berkeley
Dabaghian, Yuri dabaghia@bcm.edu CAAM, Rice University
Damineli, Daniel damineli@igc.gulbenkian.pt PhD program in Computational Biology, Instituto Gulbenkian de Ciencia
Ermentrout, Bard bard@pitt.edu Department of Mathematics, University of Pittsburgh
Fenton, Georgina stxgf@nottingham.ac.uk School of Biosciences, University of Nottingham
Fries, Pascal pascal.fries@esi-frankfurt.de Fries Lab, Max-Planck-Institut of Neurobiology
Ghitza, Oded oghitza@bu.edu Biomedical Engineering, Boston University
Giocomo, Lisa giocomo@stanford.edu Neurobiology, Stanford University
Gudmand-Høyer, Johanne joguho@ruc.dk Department of Science, Systems and Models, Roskilde University
Hasselmo, Michael hasselmo@bu.edu Psychology, Boston University
HYAFIL, Alexandre alexandre.hyafil@gmail.com DEC, ENS, Laboratoire de Neurosciences Cognitives
Kim, Jae Kyoung jaekkim@umich.edu Mathematics,
Kolchinsky, Artemy akolchin@indiana.edu Department of Informatics, Indiana University
Komek, Kubra kubrakomek@gmail.com Center for the Neural Basis of Cognition, Carnegie-Mellon University
Kopell, Nancy nk@bu.edu Department of Mathematics and Statistics, Boston University
Kotani, Kiyoshi kotani@k.u-tokyo.ac.jp Frontier Science, The university of tokyo
Lakatos, Peter plakatos@nki.rfmh.org Life Sciences, Nathan Kline Institute
Lewis, Tim tjlewis@ucdavis.edu Department of Mathematics, University of California, Davis
Lytton, William wwlytton@yahoo.com Physiology, Pharmacology, Neurology, SUNY Downstate
Nelson, Valerie VNELSON75@GMAIL.COM MATHEMATICS, Department of Defense
Netoff, Tay tnetoff@umn.edu Biomedical Engineering, University of Minnesota
Oster, Andrew osteram@gmail.com Mathematics, Case Western Reserve University
Parada, Francisco fjparada@Indiana.edu Psychological & Brain Sciences, Indiana University
Pittman-Polletta, Benjamin benpolletta@gmail.com Medicine, Harvard Medical School
Porter, Mason porterm@maths.ox.ac.uk Mathematical Institute, University of Oxford
Radulescu, Anca radulesc@colorado.edu Mathematics, University of Colorado
Rinzel, John rinzel@cns.nyu.edu Center for Neural Science & Courant Institute, New York University
Rotstein, Horacio horacio@njit.edu Mathematical Sciences, New Jersey Institute of Technology
Rubchinsky, Leonid leo@math.iupui.edu Department of Mathematical Sciences and Stark Neurosciences Research Institute at the Indiana University School of Medicine, Indiana University--Purdue University
Sedigh-Sarvestani, Madineh mus236@psu.edu Engineering Science and Mechanics, Pennsylvania State University
Shih, Chih-Wen cwshih@math.nctu.edu.tw Applied Mathematics, National Chiao Tung University
Shilnikov, Andrey ashilnikov@gsu.edu Neuroscience Institute, Georgia State University
Skinner, Frances fskinner@uhnres.utoronto.ca Toronto Western Research Institute, University Health Network
Smith, Ruth pmxrs3@nottingham.ac.uk University of Nottingham
Snyder, Abigail acs73@pitt.edu Mathematics, University of Pittsburgh
Thomas, Peter peter.j.thomas@case.edu Department of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University
Thounaojam, Umeshkanta uthoun@lsuhsc.edu Cell Biology and Anatomy, LSU Health Sciences Center, Louisiana State University
Tiesinga, Paul p.tiesinga@science.ru.nl Neuroinformatics, Radboud University Nijmegen
Toporikova, Natalia toporikovan@wlu.edu Biology, Washington and Lee University
Troyer, Todd todd.troyer@utsa.edu Biology, University of Texas
VanRullen, Rufin rufin.vanrullen@cerco.ups-tlse.fr Centre de Recherche Cerveau et Cognition, CNRS
Vinck, Martin martinvinck@gmail.com SILS Center for Neuroscience, University of Amsterdam
Wechselberger, Martin wm@maths.usyd.edu.au School of Mathematics and Statistics, University of Sydney
Wedgwood, Kyle pmxkw2@nottingham.ac.uk Mathematical Sciences, University of Nottingham
Yamazaki, Kazuo kyamazaki@math.okstate.edu Mathematics, Oklahoma State University
Zhang, Jiawei jz08@me.com Department of Mathematics, University of California, Davis
Zhou, Pengcheng pengchez@andrew.cmu.edu Center for the Neural Basis of Cognition, Carnegie-Mellon University
Response dynamics of oscillating networks, oscillatory mechanisms for selective gain control

Response dynamics of oscillating networks, oscillatory mechanisms for selective gain control

A synchronization code for space: Theory and evidence

The rodent hippocampus and cortex contain spatially tuned neurons—such as place, grid, and border cells—that are tuned to fire selectively when a rat visits specific locations in space. Such neurons are commonly assumed to implement a ‘population vector code’ which represents the animal’s position within its environment as a distributed pattern of neural firing rates. However, most spatially tuned neurons exhibit rhythmic modulation of their firing rates by 4-10 Hz theta oscillations, and the phases of such oscillations carry information about the rat’s position. Efforts to explain this observation have given rise to a class of models which posit that spatially tuned neurons may derive their position-dependent firing by detecting synchrony among theta oscillators with frequencies that vary with the animal’s movement velocity, in such a way that their phases (and thus their synchrony with one another) depend strictly upon the animal’s position in its environment. Here, I will outline one version of such a model, which posits that the rodent spatial memory system contains two major classes of neurons: rhythm generators (RGs) and synchrony detectors (SDs). It shall be hypothesized that RGs correspond to ‘theta cells’ that burst rhythmically at velocity-dependent frequencies, whereas SDs correspond to spatially tuned neurons that burst selectively at locations where they detect synchrony among a preferred subset of RGs. I will then describe results from recent experiments that have been carried out in our lab to test two key predictions of this hypothesis: 1) that the burst frequencies of theta cells vary as the cosine of the rat’s movement direction, and 2) that synchrony among pairs of simultaneously recorded theta cells vary with the rat’s position on a 2D sinusoidal grating defined over the surface of the environment.

Suppression boundaries in E-I networks, and the type of the I-cells

The synaptic interaction of excitatory and inhibitory neurons (E- and I-cells) can generate oscillations, provided that the drive to the I-cells is low enough, so that they don't get ahead of the E-cells but merely respond to them. If the drive to the I-cells is high, and inhibitory synapses are strong, the E-cells are suppressed altogether. We think about the transition from rhythmicity (low drive to the I-cells) to suppression of the E-cells (high drive to the I-cells). In work with Nancy Kopell several years ago, we suggested that this transition, if it is abrupt, could be exploited to allow the network to toggle between rhythmic activity and suppression, and that this could be useful in attentional selection. In contrast with the earlier work, here we assume that synchronization of the I-cells is always enforced by gap junctions. We find that in this case, the transition from rhythmicity to suppression is much more abrupt when the I-cells have a type 2 phase response (excitation early in the phase retards them) than when they have a type 1 phase response (excitation always accelerates them). We demonstrate this with simulations and explain it using a one-dimensional map.

Large-Scale Synchronous Beta Rhythms

Large-Scale Synchronous Beta Rhythms

Collective oscillations in networks of spiking neurons: Mechanisms and input dependence

Collective oscillations in networks of spiking neurons: Mechanisms and input dependence

The theta rhythm, spatial cognition and the hippocampus

Electrophysiological recordings from neurons in the hippocampal and entorhinal cortices of freely moving rodents provide detailed information regarding the neural representations of spatial location and orientation, and indicate a functional role for neural coding with respect to the theta rhythm of the local field potential. I will describe some of these experiments and the computational mechanisms they imply. These emphasise the roles of environmental boundaries in self-localization, via boundary vector cell firing, and temporal oscillations in the theta band in path integration, via grid cell firing. Both types of information are combined in the firing of place cells. I will describe the implications of these findings for the mechanisms supporting human spatial memory, and provide examples of electrophysiological and functional neuroimaging experiments designed to test these implications.

Neural Dynamics of Cognitive Control

Cognitive control is the ability to direct behavior in a goal-directed manner. This ability lies at the core of intelligent behaviors, allowing us to focus our limited cognitive capacity on one task while still maintaining the flexibility to quickly switch to another task as the situation (or our goals) change. I will present results on the role of frontal and parietal cortices in two forms of cognitive control: the control of attention and flexible rule use. By leveraging large-scale, multiple-region electrophysiology in non-human primates we are able to observe synchronization of neural activity within and between brain regions while animals perform these complex behaviors. I will describe results suggesting synchrony supports cognitive behaviors and how its dynamic nature may underlie cognitive flexibility.

State-dependent cortical rhythms

State-dependent cortical rhythms

Slow and Fast Gamma Rhythms in the Hippocampal Network

Brain rhythms reflect periodically synchronized electrical activity across groups of neurons and are thought to be important for neuronal communication across disparate brain regions. Gamma rhythms are a particular type of rhythm that occurs throughout many regions of the brain and have been linked to functions such as attentional selection and memory. Gamma oscillations vary in frequency (from ~25 Hz to ~ 100 Hz) from one brain region to another and also within a given brain region from one moment to the next. The exact frequency of oscillations is important because different areas will communicate most effectively when their oscillatory timing is the same. In the hippocampus, a brain region critically involved in memory operations, two distinct subtypes of gamma oscillations, slow and fast gamma, occur at different times. During slow gamma (~40 Hz), hippocampal subfield CA1 is coupled with neighboring subfield CA3, an area involved in memory retrieval. During fast gamma (~80 Hz), CA1 is coupled with the entorhinal cortex, a region transmitting information about the current environment. In this lecture, I will present new data supporting the hypothesis that slow and fast gamma rhythms serve different functions, namely that slow gamma facilitates memory retrieval and fast gamma promotes memory encoding.

Distinct top-down and bottom-up attention networks revealed through high-resolution electrocorticography

Brain-wide networks operating at a millisecond timescale are thought to underlie our cognitive functions, but have never been observed directly. Neuroimaging studies based on hemodynamic signals visualized the precise topographies of brain-wide functional networks, but at low temporal resolution. Neurons and areas within these networks likely cooperate through rhythmic synchronization in multiple frequency bands. However, limitations of current recording methods have restricted our ability to detect and investigate these putative brain-wide synchronization networks. Only if extended corticocortical synchronization networks are observed directly and in behaving subjects, will we simultaneously reveal their topographies, frequencies, directions of information flow and cognitive functions, and thereby the relations among those properties. I will present data from large-scale, high-density electrocorticography grids, combining millisecond temporal and millimeter spatial resolution with coverage of large parts of one hemisphere. I will show that a given brain area may simultaneously participate in different networks that synchronize in distinct frequencies and mediate influences in counter-streams. A gamma-band (50 90 Hz) network synchronizes visual-occipital areas and parts of parietal cortex, and gamma-mediated inter-areal influences are bottom-up. A beta-band (peaking at 14 18 Hz) network synchronizes parietal and frontal areas and parts of visual cortex, and beta-mediated inter-areal influences are mostly top-down. Both networks subserve the cognitive function of attention: gamma- and beta-mediated inter-areal influences are enhanced when they mediate behaviorally relevant signals. The direct topographical demonstration of rhythmic synchronization-defined networks constitutes a new quality of brain network investigation and opens an important window onto their function.

On the central role of theta in decoding speech

On the central role of theta in decoding speech

Mechanisms underlying medial entorhinal cortex topography

A core goal of neuroscience is to determine how sensory inputs map to neural circuits and form functional cortical architectures. Recently, our understanding of the neural representation of space by medial entorhinal cortical neurons has evolved to the point of providing a unique opportunity to determine the mechanisms and function of circuit organization in a region highly associated with spatial navigation and memory. My research has specifically concentrated on the mechanisms underlying the representation of space by medial entorhinal cortex neurons called ‘grid cells’. A strong characteristic of grid cells is their spatial scale, which is organized topographically, increasing progressively from dorsal to ventral medial entorhinal cortex. I have focused on unraveling the potential substrates underlying this topographical expansion of grid scale. In addition, our recent work has highlighted the presence of a topographic gradient in another functionally-defined medial entorhinal cell type; the head direction cell.

Oscillations and grid cells in entorhinal cortex

Oscillations and grid cells in entorhinal cortex

Theta-gamma nested oscillations in speech perception

Theta-gamma nested oscillations in speech perception

Brain Rhythms Facilitate Bottom-Up and Top-Down Processing

It is well known that the brain produces rhythms at many different frequencies and combination of frequencies, and that these rhythms are associated with different cognitive states and tasks. It is still mysterious, however, how the rhythms take part in function. This talk discusses two working hypotheses about this issue.

  1. Clues to the function of rhythms come from the physiology underlying the rhythms (Function Follows Physiology). That is, it is not just the frequency that matters, but also the mechanistic bases of rhythms that matter in their functional applications. In particular, cortical layers are critical.
  2. The ways in which rhythms support function are complex; they are not apt to be obvious from data, and require modeling to form hypotheses.

These themes are illustrated with examples involving bottom-up and top-down processing, including cortical and thalamic rhythms.

The role of oscillatory entrainment in auditory selective attention

The role of oscillatory entrainment in auditory selective attention

Theta gamma coordination in setting of psychomimetics and other modulatory interventions

Theta gamma coordination in setting of psychomimetics and other modulatory interventions

Gaining insight from theoretically-inspired biologically-based models

It is clear that we need mathematical models and analyses of them to understand brain dynamics. However, in building our mathematical models of neuronal networks, it is not clear what data, how much data, and what level(s) of detail are most appropriate to use. Furthermore, it is clear that cellular characteristics need to be considered in our models as experiments continue to show cellular specificity in affecting network output. However, network size and connectivity also have to be taken into consideration. In this talk, I will present our work examining the generation of gamma rhythms in models of fast-spiking inhibitory cell networks. These models are based on CA1 hippocampus considering an ING-type mechanism and using the experimental context of a whole hippocampus preparation exhibiting spontaneous population activities. Consideration of these aspects together leads to the requirement of weak inhibitory connections between fast-spiking cells and strong excitatory drives to them for coherent gamma rhythms to emerge. Most interestingly, a sharp transition in gamma coherence is found for small changes in excitatory drive, thus suggesting a potential design property underlying theta/gamma rhythms. It is important to note that without the experimental context and constraints, this does not arise. Our work thus illustrates how a mathematical mechanism coupled with a well-defined experimental context could lead to biological insights.

Oscillations and neural coding

Oscillations and neural coding

Perceptual and attentional rhythms

Neuronal communication between cortical areas heavily relies on oscillatory, periodic mechanisms whose precise timing critically determines the flow of information. Yet little is known about the perceptual and psychological consequences of such periodic neuronal dynamics at the rapid time scale of the oscillatory cycle: what perceptual changes accompany the drastic changes of neuronal activity observed between opposite phases of the cycle? I will show several experimental examples of these perceptual consequences in the visual domain. To summarize, visual perception and attention seem to wax and wane intermittently at frequencies in the theta (~7Hz) and alpha (~10Hz) range, possibly reflecting the underlying periodic neuronal processes. Based on spiking neural network simulations, I will argue that similar perceptual cycles can also exist at higher frequencies (gamma range), and that our perceptual experience may be the result of cross-frequency interactions between these different rhythms

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The role of oscillatory entrainment in auditory selective attention
Peter Lakatos

The role of oscillatory entrainment in auditory selective attention

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Large-Scale Synchronous Beta Rhythms
Steve Bressler

Large-Scale Synchronous Beta Rhythms

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Theta-gamma nested oscillations in speech perception
Alexandre HYAFIL

Theta-gamma nested oscillations in speech perception

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Theta gamma coordination in setting of psychomimetics and other modulatory interventions
William Lytton

Theta gamma coordination in setting of psychomimetics and other modulatory interventions

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On the central role of theta in decoding speech
Oded Ghitza

On the central role of theta in decoding speech

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Perceptual and attentional rhythms
Rufin VanRullen

Neuronal communication between cortical areas heavily relies on oscillatory, periodic mechanisms whose precise timing critically determines the flow of information. Yet little is known about the perceptual and psychological consequences of such pe

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Collective oscillations in networks of spiking neurons: Mechanisms and input dependence
Nicolas Brunel

Collective oscillations in networks of spiking neurons: Mechanisms and input dependence

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Suppression boundaries in E-I networks, and the type of the I-cells
Christoph Borgers

The synaptic interaction of excitatory and inhibitory neurons (E- and I-cells) can generate oscillations, provided that the drive to the I-cells is low enough, so that they don't get ahead of the E-cells but merely respond to them. If the driv

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Oscillations and grid cells in entorhinal cortex
Michael Hasselmo

Oscillations and grid cells in entorhinal cortex

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The theta rhythm, spatial cognition and the hippocampus
Neil Burgess

Electrophysiological recordings from neurons in the hippocampal and entorhinal cortices of freely moving rodents provide detailed information regarding the neural representations of spatial location and orientation, and indicate a functional role